Data Scientist - Hyperforce Development Platform Support
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Job CategorySoftware Engineering
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Join us if you are interested in developing data science solutions to make a meaningful impact in improving developer productivity! We are looking to hire experienced data scientists with a strong sense of service ownership, ability to contribute to design and quickly absorb solutions, empathy for customers, excellent communication skills, a drive for continuous improvement. The role will entail overseeing the entire lifecycle of data-science and ML solutions from POC to deployment to ongoing maintenance and enhancement. Our team creates and supports several existing ML products such as a customer support generative AI chatbot, semantic search, error identification, customer support dashboards, etc.
The HDPS Customer Success team is distributed across North America, IST, and DUB. This role will be based In the Bay Area.
Salesforce Hyperforce Development Platform Support (HDPS) develops and hosts the Falcon continuous delivery and deployment platform. This includes the Spinnaker, PCS, FIT and IAC services, the CD platform and ecosystem around it and a suite of software integrity and distribution services.
The HDPS Customer Success team owns consulting with and assisting Salesforce engineers adopt and use HDPS services and capabilities successfully. This includes working with customers to help them onboard to (new capabilities in) the platform, diagnosing and debugging issues, developing and delivering training content, assessing and driving creation of documentations, designing and developing customer-facing solutions and automation like analytics dashboards and ML-based classification of errors.
Required Skills (Data Scientist):
- A Master’s degree in Computer Science, Computer Engineering, Electrical Engineering, Operations, Statistics, Data Science or other relevant courses and 3+ years of prior relevant experience
- Demonstrated expertise with reporting tools like MS Excel and at least one among the following: Python (Pandas), R, SAS, etc. Experience with ML concepts and statistical libraries like pandas, matplotlib, numpy, sklearn (or their equivalents) is required
- Demonstrated ease with querying languages like SQL (SOQL / SAQL is a plus)
- Demonstrated experience with at least one visualization tool and one library from - Tableau, Tableau CRM,Power BI, D3, Apache e-charts, Streamlit, Gradio, R-Shiny, Dash, etc.
- Demonstrated experience with ETL pipelines and workflows - Jenkins / Airflow / any other ETL orchestration framework
- Demonstrated experience with Deep learning concepts and NLP frameworks such as nltk, pytorch, tensorflow, keras, huggingface, sentence_transformers, etc.
- Is a self-starter, must know how to approach problems in a structured and timely fashion
- Excellent presentation and analytical skills. Ability to learn fast, work collaboratively, and respond to broad problem statements in a data-driven manner
- Able to structure long-term project roadmaps, resolve inter-team dependencies, and work with stakeholders and ensure timely delivery of project milestones and deliverables
Preferred Skills (Data Scientist):
- Prior experience of deploying ML applications on cloud ecosystems like AWS or GCP, and monitoring / enhancing systems in an ongoing fashion
- Experience with data modeling on RDS / DynamoDB / Hive etc.
- Experience with LLMs, prompt engineering, fine tuning and libraries like Langchain
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